Triple
T18933801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo Díaz |
E463186
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Díaz |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Díaz | Statement: [Guillermo Díaz, familyName, Díaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Díaz Context triple: [Guillermo Díaz, familyName, Díaz]
-
A.
Díaz
chosen
Díaz is a common Spanish surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
-
B.
Altamirano
Altamirano is a municipality in the Mexican state of Chiapas known for its significant Indigenous Tzeltal population and role in regional social and political movements.
-
C.
Doroteo
Doroteo is the given name of Doroteo Guamuch Flores, a renowned Guatemalan long-distance runner and Boston Marathon champion.
-
D.
Juárez
Juárez is a major Mexican border city in the state of Chihuahua, located across the Rio Grande from El Paso, Texas, and known for its manufacturing industry and strategic trade position.
-
E.
Juárez
Juárez is a Mexico City Metro station on Line 3 located near the historic center, serving the bustling Juárez neighborhood and surrounding commercial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e57e648190aa4d3b09e84d4d38 |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.